Evidence-based surveillance protocol for vestibular schwannomas: a long-term analysis of tumor growth using conditional probability.

ABSTRACT

OBJECTIVE: The growth characteristics of vestibular schwannomas (VSs) under surveillance can be studied using a Bayesian method of growth risk stratification by time after surveillance onset, allowing dynamic evaluations of growth risks. There is no consensus on the optimum surveillance strategy in terms of frequency and duration, particularly for long-term growth risks. In this study, the long-term conditional probability of new VS growth was reported for patients after 5 years of demonstrated nongrowth. This allowed modeling of long-term VS growth risks, the creation of an evidence-based surveillance protocol, and the proposal of a cost-benefit analysis decision aid. METHODS: The authors performed an international multicenter retrospective analysis of prospectively collected databases from five tertiary care referral skull base units. Patients diagnosed with sporadic unilateral VS between 1990 and 2010 who had a minimum of 10 years of surveillance MRI showing VS nongrowth in the first 5 years of follow-up were included in the analysis. Conditional probabilities of growth were calculated according to Bayes' theorem, and nonlinear regression analyses allowed modeling of growth. A cost-benefit analysis was also performed. RESULTS: A total of 354 patients were included in the study. Across the surveillance period from 6 to 10 years postdiagnosis, a total of 12 tumors were seen to grow (3.4%). There was no significant difference in long-term growth risk for intracanalicular versus extracanalicular VSs (p = 0.41). At 6 years, the residual conditional probability of growth from this point onward was seen to be 2.28% (95% CI 0.70%-5.44%); at 7 years, 1.35% (95% CI 0.25%-4.10%); at 8 years, 0.80% (95% CI 0.07%-3.25%); at 9 years, 0.47% (95% CI 0.01%-2.71%); and at 10 years, 0.28% (95% CI 0.00%-2.37%). Modeling determined that the remaining lifetime risk of growth would be less than 1% at 7 years 7 months, less than 0.5% at 8 years 11 months, and less than 0.25% at 10 years 4 months. CONCLUSIONS: This multicenter study evaluates the conditional probability of VS growth in patients with long-term VS surveillance (6-10 years). On the basis of these growth risks, the authors posited a surveillance protocol with imaging at 6 months (t = 0.5), annually for 3 years (t = 1.5, 2.5, 3.5), twice at 2-year intervals (t = 5.5, 7.5), and a final scan after 3 years (t = 10.5). This can be used to better inform patients of their risk of growth at particular points along their surveillance timeline, balancing the risk of missing late growth with the costs of repeated imaging. A cost-benefit analysis decision aid was also proposed to allow units to make their own decisions regarding the cessation of surveillance.